1. Field of the Invention
The invention relates generally to oil and gas exploration, particularly to methods and systems for deriving formation properties from formation logging data.
2. Background Art
Various well logging techniques are known in the field of hydrocarbon and water exploration and production. These techniques typically employ logging or downhole tools (sondes) equipped with sources adapted to emit energy through a borehole traversing the subsurface formation. The emitted energy interacts with the surrounding formation to produce signals that are detected and measured by one or more sensors on the instrument. By processing the detected signal data, a profile of the formation properties is obtained.
Subsurface or downhole logging techniques are realized in different ways as known in the art. A well tool, comprising a number of transmitting and detecting devices for measuring various parameters, can be lowered into a borehole on the end of a cable or wireline. The cable, which is attached to some mobile processing center at the surface, is the means by which parameter data may be sent up to the surface. With this type of logging, it becomes possible to measure borehole and formation parameters as a function of depth, i.e., while the tool is being pulled uphole.
An alternative to wireline logging techniques is the collection of data on downhole conditions during the drilling process. By collecting and processing such information during the drilling process, the driller can modify or correct key steps in the operation to optimize performance. Schemes for collecting data of downhole conditions and movement of the drilling assembly during the drilling operation are known as measurement-while-drilling (MWD) techniques. Similar techniques focusing more on measurement of formation parameters than on movement of the drilling assembly are known as logging-while-drilling (LWD). Note that drilling operations may also use casings or coil tubings instead of conventional drill strings. Casing drilling and coil tubing drilling are well known in the art. In these situations, logging operations may be similarly performed as in conventional MWD or LWD. In this description, “logging-while-drilling” will be generally used to include the use of a drill string, a casing, or a coil tubing, and hence MWD and LWD are intended to include operations using casings or coil tubings. Logging-while-tripping (LWT) is an alternative to LWD and MWD techniques. In LWT, a small diameter “run-in” tool is sent downhole through the drill pipe, at the end of a bit run, just before the drill pipe is pulled. The run-in tool is used to measure the donwhole physical quantities as the drill string is extracted or tripped out of the hole. Measured data is recorded into tool memory versus time during the trip out. At the surface, a second set of equipment records bit depth versus time for the trip out, and this allows the measurements to be placed on depth. Sensors or tools permanently placed in a wellbore may also be used to obtain log data. Embodiments of the invention may use data obtained with any of these different logging methods.
FIG. 1 shows a typical LWD system that includes a derrick 10 positioned over a borehole 11. A drilling tool assembly, which includes a drill string 12 and drill bit 15, is disposed in the borehole 11. The drill string 12 and bit 15 are turned by rotation of a Kelly 17 coupled to the upper end of the drill string 12. The Kelly 17 is rotated by engagement with a rotary table 16 or the like forming part of the rig 10. The Kelly 17 and drill string 12 are suspended by a hook 18 coupled to the Kelly 17 by a rotatable swivel 19. Drilling fluid (mud) 6 is stored in a pit 7 and is pumped through the center of the drill string 12 by a mud pump 9 to flow downwardly. After circulation through the bit 15, the drilling fluid circulates upwardly through an annular space between the borehole 11 and the outside of the drill string 12. Flow of the drilling mud 6 lubricates and cools the bit 15 and lifts drill cuttings made by the bit 15 to the surface for collection and disposal. As shown, a logging tool 14 is connected to the drill string 12. Signals measured by the logging tool 14 may be transmitted to the surface computer system 13 or stored in memory (not shown) onboard the tool 14. The logging tool 14 may include any number of conventional sources and/or sensors known in the art.
Formation logging data, whether from wireline, LWD, MWD, or LWT operations, are then processed to derive formation properties (formation profiles). Various techniques are known for deriving formation properties from the measurement data. Some of these techniques are specific to the types of measurement data (e.g., sonic data, resistivity data, NMR data, neutron data, gamma ray data, etc.). A common technique used to extract formation properties from measurement data involves an inversion process, which in essence attempts to find an inverse response function of the tool used in the measurements.
Formation logging data acquired with a sensor depends on not only the formation properties (profiles), but also the response function of the sensor. If the sensor response function, or its inverse (i.e., the inverse sensor response function), is known, then the formation profile may be deconvolved from the measurement data. Such a process of deriving formation properties directly from the measurement data is referred to as an inversion process.
An alternative to the inversion process is sometimes called “forward modeling.” In this approach, a particular formation model is assumed. The formation model includes various layers, each having a set of properties (parameters). The tool responses are then calculated based on the formation model. The computed tool responses are then compared with the actual tool responses. An iterative process is then used to alter formation model parameters in order to minimize the difference between the computed tool responses and the actual tool responses. The modeling method is efficient when only a limited parameters are to be optimized. However, this approach can become very inefficient and time consuming when a large number of formation parameters are to be derived.
While the above described methods are useful in deriving formation properties from measurement data, there still exists a need for other methods and systems that can efficiently provide estimates of formation properties from the measurement data.